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Economic analyses of breast cancer control in low- and middle-income countries: a systematic review



To support the development of global strategies against breast cancer, this study reviews available economic evidence on breast cancer control in low- and middle-income countries (LMICs).


A systematic article search was conducted through electronic scientific databases, and studies were included only if they concerned breast cancer, used original data, and originated from LMICs. Independent assessment of inclusion criteria yielded 24 studies that evaluated different kinds of screening, diagnostic, and therapeutic interventions in various age and risk groups. Studies were synthesized and appraised through the use of a checklist, designed for evaluating economic analyses.


The majority of these studies were of poor quality, particularly in examining costs. Studies demonstrated the economic attractiveness of breast cancer screening strategies, and of novel treatment and diagnostic interventions.


This review shows that the evidence base to guide strategies for breast cancer control in LMICs is limited and of poor quality. The limited evidence base suggests that screening strategies may be economically attractive in LMICs – yet there is very little evidence to provide specific recommendations on screening by mammography versus clinical breast examination, the frequency of screening, or the target population. These results demonstrate the need for more economic analyses that are of better quality, cover a comprehensive set of interventions and result in clear policy recommendations.

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Noncommunicable diseases (NCDs) have become increasingly important in low- and middle-income countries (LMICs). Once considered a problem only in high-income countries (HICs), more and more patients who suffer from cancers and other NCDs are now observed in LMICs [1]. This is mainly due to the ageing populations and changing lifestyles in LMICs [2]. The global importance of NCDs has recently been acknowledged through the UN Summit on NCDs, held by the UN General Assembly in September 2011. As highlighted in the summit, the most prominent cause of cancer death among women in LMICs is breast cancer, accounting for 269,000 deaths (12.7% of all cancer deaths) in 2008 [3, 4].

In HICs, many efforts have been undertaken to control breast cancer, leading to various improvements in breast cancer outcomes [5, 6]. Strategies for breast cancer control are geared towards early detection and early treatment, and although its benefits are still open to discussion [79], mammography screening has been widely implemented [1012]. In these countries, the selection of breast cancer control strategies has often been guided by economic analyses, demonstrating the value of alternative interventions [1316].

In contrast to the established breast cancer control strategies in HICs, breast cancer is often neglected in LMICs and control strategies lack evidence-based information [1720]. Policy-makers in LMICs cannot adopt similar breast cancer control strategies as implemented in HICs because most LMICs rely on much smaller budgets, and both the costs and effectiveness of control strategies are highly dependent on the population characteristics and the functioning of the health system [11, 20, 21].

Against this background, the present review provides an inventory of economic analyses of breast cancer control in LMICs. The paper’s objectives are to present the available economic evidence from LMICs and to assess the methodological quality of the analyses. This research could improve the evidence base on cost-effective breast cancer interventions and could strengthen breast cancer control policy in LMICs.


Search strategy and selection criteria

In this review, we analyzed publications from the MEDLINE index using PubMed, the Web of Science, Scopus, and Google Scholar. We searched the literature using the keyword ‘breast cancer’, combined with the keywords: ‘developing countries’, ‘Asia’, ‘USSR’, ‘Middle-East’, ‘Eastern Europe’, ‘West-Indies’, ‘China’, ‘Russia’, ‘India’, ‘Africa’, or ‘limited resource’, or combined with: ‘cost-benefit’, ‘cost-effectiveness’, ‘costing’, or ‘cost analysis’. Additionally, we searched these indexes using ‘breast neoplasms’, ‘developing countries,’ and ‘economics’ in MeSH terms. Our search took place in January 2013, and was limited to publications in English. Studies were included only if they concerned breast cancer and originated from LMICs as listed by The World Bank [22].

The selection process is shown in Figure 1. In step 1, articles found by our search in the various indexes were merged in a database, which was then corrected for duplications (in Google Scholar, because of the large number of articles founds, we screened titles until the point that we did not find any further relevant title among the last 500 screened titles; in total, we screened 800 titles in this database). In step 2 we screened the titles of these articles, in step 3 the abstracts and in step 4 the remaining articles were read completely. We excluded publications for which no full-text article versions were available, or those not published in English. Furthermore, we excluded articles that only mentioned costs or cost-effectiveness without presenting original data.

Figure 1
figure 1

Prisma statement 1: Prisma 2009 flow diagram.

Study characteristics

We documented the following characteristics from the reviewed articles: country or region, base year of cost data, study population, and breast cancer stage(s) considered. The stage was categorized as stage I to IV according to the American Joint Committee on Cancer [23].

We documented the following methodological characteristics: type of economic evaluation –cost analysis or cost of illness analysis, separately reported costs and effects, cost-effectiveness analysis, cost–benefit analysis, and cost–utility analysis; study design – experimental, observational (cohort, case control, or cross-sectional), model based, and other designs; study perspective – non-healthcare perspective (for example, productivity loss, travel costs, co-payments), healthcare perspective (for example, hospital administration costs, treatment costs), and societal perspective including non-healthcare and healthcare costs; time horizon; and outcome measure for effectiveness (disability-adjusted life years, quality-adjusted life years, life years saved, lives saved, and intermediate outcome measures).

The following qualitative characteristics were documented: sources for estimation of effectiveness, sources for estimation of resource utilization, discount rates used, sensitivity analysis for assumptions, and reported incremental analysis. We classified sources for estimation of effectiveness and resource utilization by primary data collection (for example, patients, questionnaires), secondary data collection (for example, records), literature based, expert opinion, and other. We also noted whether discount rates were used on costs, effects, both costs and effects, or not at all.

We also registered the study objective, the evaluated interventions, and the main study conclusions for each reviewed article.

Study evaluation

We used an established checklist by Drummond and Jefferson to judge the quality of the economic evaluations [24, 25]. A three-point response scale was added, similar to Gerard and colleagues [25], to more specifically grade the quality of each item on the checklist. Scores on this scale ranged from 0 (not considered), to 1 (partially considered) to 2 (fully considered). A few adjustments to the checklist by Drummond and Jefferson were necessary to create a more responsive scoring system for our particular set of economic studies. We removed those items that were not applicable to any of the reviewed studies (for example, on productivity changes), and combined some items that were otherwise putting too much emphasis to certain domains in the overall score (for example, on health state valuations and discount rates). The adapted checklist is provided in Table 1. We summed up all scores, and compared this with the maximum attainable score to calculate the mean quality score of a study (as a percentage of the maximum attainable score). We accounted for items that were not relevant to the study under scrutiny (for example, studies that studied costs and effects in a single year were not criticized for not applying any discount rate in the analyses).

Table 1 Checklist for quality of economic evaluations

Two reviewers (SGZ and RMB) evaluated each publication for conformance with this checklist, and consensus was reached when scores differed. We followed PRISMA guidelines for reporting this systematic review.


Search results

The stepwise selection of articles by our selection criteria is presented in Figure 1. Our search strategy resulted in a total of 6,816 studies: 679 studies from PubMed, 328 studies from Web of Science, 5,009 studies from Scopus, and 800 from Google Scholar, respectively. In step 1, by merging the results of all individual search strategies and excluding duplication, the total number of hits was reduced to almost 4,400. Upon screening of titles (step 2), abstracts (step 3) and full texts (step 4), we eventually identified 24 articles that met our inclusion criteria.

Study characteristics

Table 2 describes the baseline characteristics of the 24 included studies. We found eight studies from Asia, most concerning China, India and Iran. Five studies were on a global or sub-regional level, while there were five studies from Africa, three from Europe and three from Latin America. A total of 10 studies evaluated breast cancer screening in combination with treatment (n = 10), assessing mammography screening (n = 9), clinical breast examination (CBE) (n = 3), magnetic resonance imaging (n = 1), ultrasound (n = 1), biopsy (n = 1), elasticity imaging (n = 1), and tactile imaging (n = 1), respectively [2636]. These studies evaluated a variety of age groups and screening frequencies (Table 3). One study reported on a mass-media intervention to improve the early detection of breast cancer in Ghana [35]. Seven studies evaluated only treatment interventions including drug therapy (n = 4), oophorectomy (n = 1), radiotherapy (n = 1), and treatment in general (n = 1) [3742]. Other studies examined the costs of diagnostic interventions (n = 3) or did not consider a specific intervention (n = 2) [4348].

Table 2 Characteristics of reviewed studies, ordered by base year of cost data
Table 3 Interventions compared, study objectives, and main study conclusions of reviewed articles

The methodological study characteristics of the reviewed studies are presented in Table 2. The base year of cost data in the included studies was generally not from before year 2000, and could not be identified in eight studies. The majority of studies combined both costs and effects in a single cost-effectiveness estimate (n = 13), and the majority of these were based on mathematical models (n = 9). Most studies used a healthcare perspective (n = 19), and only one study included non-healthcare costs [48]. Studies used a time horizon varying between 5 weeks and the lifetime of the study population. Most reviewed studies used intermediate outcome measures (that is, clinical effects n = 8), life years saved (n = 6), or disability-adjusted life years (n = 5) as their main effectiveness outcome, while quality-adjusted life years were less frequently used (n = 3).

Study quality

Table 4 summarizes the quality of the included studies, as indicated by the percentage score. The quality of all studies ranges from 23 to 86%. Studies by Ginsberg and colleagues, Zelle and colleagues, and Bai and colleagues had the highest total average scores, and these were all modeling studies [27, 35, 42]. If items were not applicable (NA) for a reviewed paper, the maximum obtainable (domain) score was reduced with 2 points per item.

Studies generally scored poorly on the domain ‘estimation of costs’, at an average 34% of the maximum obtainable score across all studies. The average score for ‘study design’ was 73%, while the quality of the domains ‘estimation of effectiveness’, ‘analysis’, and ‘interpretation of results’ was scores as 70%, 51%, and 68%, respectively.

Study findings

As described earlier, most studies evaluated breast cancer screening in combination with treatment. Studies in Mexico, Poland, Turkey identified mammography screening as a cost-effective intervention [31, 33, 34, 36], whereas studies in India, Ghana and Egypt found other strategies (such as CBE screening or mass-media awareness raising) to be economically more attractive (Table 3) [26, 30, 35]. Sarvazyan and colleagues proposed another breast cancer screening option: tactile imaging as an alternative to several other interventions [32].

Table 4 Summary of quality assessment and domain scores of reviewed studies

Studies evaluating treatment interventions typically favored the novel interventions. Anastrozole was more cost-effective than tamoxifen in a Brazilian study [38], oophorectomy and tamoxifen after recurrence was shown to be favorable in Vietnamese and Chinese patients [40], additional radiotherapy after breast-conserving surgery was very cost-effective in China [42], and chemotherapy consisting of a docetaxel and cyclophosphamide regimen was more attractive compared with an doxorubicin and cyclophosphamide regimen also in Chinese patients [39]. There was only one study with a negative suggestion for the novel and more costly intervention docetaxel, doxorubicin, cyclophosphamide, as compared with the more conventional 5-fluorouracil, doxorubicin, dyclophosphamide regime [49].

Studies that only assessed costs and did not include effectiveness estimates, reported on costs of breast cancer for patient management in Brazil (US$1,646 per patient) [43], and the costs of patient expenditure (US$242 per patient) in India [48].

The three studies evaluating diagnostic interventions demonstrated the economic attractiveness of inexpensive interventions; that is, fine-needle aspiration cytology and methylene blue dye injections [4547]. These interventions could be especially relevant for diagnosing breast cancer in rural settings and settings with low resources.


This study shows that there is limited economic evidence on breast cancer control in LMICs. Only 24 economic evaluation studies were found in this review, and their quality was generally poor. Furthermore, the study populations were very diverse, as most studies examined different kinds of screening and therapeutic interventions in various age and risk groups. Owing to this poor availability, quality, and comparability, we conclude that the economic evidence base to guide strategies for breast cancer in LMICs is currently insufficient.

Our review raises a few discussion points. First, there is mixed evidence on the economic attractiveness of mammography screening. Studies in Mexico, Poland and Turkey demonstrate the intervention to be cost-effective, whereas studies in India, Ghana, and Egypt suggests that other forms of screening – for example, by CBE – provide more value for money. The evidence base is too small to generalize these findings to other LMICs, and to draw general conclusions. Also, most of the studies evaluating therapeutic interventions seem to favor the more novel – and often more expensive – therapy. These findings may be explained by many reasons, including the higher effectiveness of the novel interventions but possibly also the association between funding sources and pro-industry conclusions [50].

Second, in general, we found that the quality of the reviewed articles was poor. The majority of studies failed to score at least 50% on every domain (‘study design’, ‘estimation of effectiveness’, ‘estimation of costs’, ‘analysis’, and ‘interpretation of results’). These domain scores further show that most emphasis was given to the design of the studies and the interpretation of results, whereas costs, in particular, were poorly evaluated. This calls for better adherence of studies to methodological standards for economic analyses, or the development of such standards specifically for breast cancer research. Future studies could be improved by using a checklist, and through transparent reporting of the items in checklists [25, 51].

Third, the current evidence base leaves many LMICs with the difficult task of extrapolating results from other countries. The transferability of economic evaluations across countries is complicated, as clinical practice patterns, healthcare systems, and cultural and ethical practices differ across countries [52, 53]. Standardized ways of adopting economic evaluations, with the help of available checklists and guidelines [24, 25, 51, 5458], may improve this lack of transferability. Alternatively, modeling studies could play an important role in extrapolating results from one context to another. Modeling studies, however, rely on the availability of costing and effectiveness data, and this emphasizes the need for more primary data collection on these aspects in LMICs. With data from such studies, researchers would not have to continue to rely on sensitivity analyses or extrapolating cost estimates from data in HICs. National cancer registries, mortality databases, hospital registries, and accessible publications would be essential for providing such information [59].

Fourth, and closely related, we generally advocate the use of modeling studies in the economic analysis of breast cancer control in LMICs. In addition to their use in the extrapolation of study findings, they generally appeared to be of high quality, are sufficiently flexible to include important methodological characteristics such as adequate time horizon, and seem also appropriate to evaluate a broad array of interventions across different groups.

Fifth, the most adopted type of economic evaluation was cost-effectiveness analysis, using a healthcare perspective and life years saved as the primary outcome. Although cost-effectiveness analyses using a healthcare perspective contribute very important information, productivity losses for patients suffering from breast cancer – and most probably other NCDs – can be substantial [60, 61]. So far, there is no methodological consensus on estimating productivity loss and the cost of illness can vary greatly between different costing approaches (for example, human capital approach vs. friction cost approach) and also between gender, age and the type of job of patients [62]. Further research should account for economic and social characteristics of the population under study, and should try to investigate productivity losses. Additionally, life years saved may be a less appropriate outcome when palliative or preventive interventions are investigated, and the use of disability-adjusted or quality-adjusted life years may be more appropriate.

Sixth, there is currently very little economic evidence on less established interventions such as tactile imaging, awareness raising, CBE screening, or preventive and palliative interventions. Economic studies, especially in LMICs, should aim to evaluate these interventions more often (and thereby including broad target populations) as they have the potential to be economically attractive [26, 30, 32, 35].

Finally, guidance in decision-making and recommendations for implementation are generally underemphasized in economic evaluations. By reflecting on the health system characteristics of the particular country and considering them in implementation recommendations, economic evaluations could improve their use in breast cancer policy development.

Our study has a number of limitations. Primarily, the number of articles reviewed is very limited, possibly the result of our search strategy. Besides a possible publication bias – studies with negative outcomes are less likely to be published – we searched only for articles published in English. This may explain the relatively small number of articles found, for instance, from Spanish-speaking regions or from countries where there is less emphasis on publishing research (for example, in Africa). Also, the studies included in our review vastly differed with regard to their methodology, objectives, characteristics, and study populations and hence are difficult to compare. In addition, our quality assessment of the reviewed articles was based on a checklist that gives highest scores to a full reporting of all domains. However, short reports in the form of, for example, editorials may not include all these details but may nevertheless be valid for the goals they serve. Hence, the scores for these studies should be interpreted with caution.


To conclude, our findings indicate that research on the costs and cost-effectiveness of breast cancer control in LMICs is still in its infancy. The limited evidence base suggests that screening strategies may be economically attractive in LMICs – yet there is very little evidence to provide specific recommendations (on screening by mammography vs. CBE, the frequency of screening, or the target population). These results demonstrate the need for more economic analysis that are uniform, of better quality, cover a comprehensive set of interventions and result in clear policy recommendations.



Clinical breast examination


High-income country


Low- and middle-income country


Noncommunicable disease.


  1. Abegunde DO, Mathers CD, Adam T, Ortegon M, Strong K: The burden and costs of chronic diseases in low-income and middle-income countries. Lancet. 2007, 370: 1929-1938. 10.1016/S0140-6736(07)61696-1.

    Article  PubMed  Google Scholar 

  2. Beaglehole R, Bonita R, Horton R, Adams C, Alleyne G, Asaria P, Baugh V, Bekedam H, Billo N, Casswell S, Cecchini M, Colagiuri R, Colagiuri S, Collins T, Ebrahim S, Engelgau M, Galea G, Gaziano T, Geneau R, Haines A, Hospedales J, Jha P, Keeling A, Leeder S, Lincoln P, McKee M, Mackay J, Magnusson R, Moodie R, Mwatsama M, Lancet NCDAG, Alliance NCD: Priority actions for the non-communicable disease crisis. Lancet. 2011, 377: 1438-1447. 10.1016/S0140-6736(11)60393-0.

    Article  PubMed  Google Scholar 

  3. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM: Estimates of worldwide burden of cancer in 2008: GLOBOCAN. Int J Cancer. 2008, 127: 2893-2917.

    Article  Google Scholar 

  4. The good news about cancer in developing countries. Lancet. 2011, 378: 1605-10.1016/S0140-6736(11)61681-4.

  5. Jemal A, Thun MJ, Ries LA, Howe HL, Weir HK, Center MM, Ward E, Wu XC, Eheman C, Anderson R, Ajani UA, Kohler B, Edwards BK: Annual report to the nation on the status of cancer, 1975–2005, featuring trends in lung cancer, tobacco use, and tobacco control. J Natl Cancer Inst. 2008, 100: 1672-1694. 10.1093/jnci/djn389.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Levi F, Lucchini F, Negri E, La Vecchia C: Continuing declines in cancer mortality in the European Union. Ann Oncol. 2007, 18: 593-595.

    Article  CAS  PubMed  Google Scholar 

  7. Duffy SW, Tabar L, Olsen AH, Vitak B, Allgood PC, Chen TH, Yen AM, Smith RA: Absolute numbers of lives saved and overdiagnosis in breast cancer screening, from a randomized trial and from the Breast Screening Programme in England. J Med Screen. 2010, 17: 25-30. 10.1258/jms.2009.009094.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gotzsche PC, Hartling OJ, Nielsen M, Brodersen J, Jorgensen KJ: Breast screening: the facts – or maybe not. BMJ. 2009, 338: b86-10.1136/bmj.b86.

    Article  PubMed  Google Scholar 

  9. Kopans DB, Smith RA, Duffy SW: Mammographic screening and ‘overdiagnosis’. Radiology. 2011, 260: 616-620. 10.1148/radiol.11110716.

    Article  PubMed  Google Scholar 

  10. Boyle P, Levin B: World Cancer Report 2008. 2008, Lyon: International Agency for Research on Cancer (IARC)

    Google Scholar 

  11. Coleman MP, Forman D, Bryant H, Butler J, Rachet B, Maringe C, Nur U, Tracey E, Coory M, Hatcher J, McGahan CE, Turner D, Marrett L, Gjerstorff ML, Johannesen TB, Adolfsson J, Lambe M, Lawrence G, Meechan D, Morris EJ, Middleton R, Steward J, Richards MA: Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International Cancer Benchmarking Partnership): an analysis of population-based cancer registry data. Lancet. 2011, 377: 127-138. 10.1016/S0140-6736(10)62231-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Vainio H, Bianchini F: IARC Handbook of Cancer Prevention. Breast Cancer Screening. 2002, Lyon: IARC Press, 7

    Google Scholar 

  13. De Koning HJ: Breast cancer screening; cost-effective in practice?. Eur J Radiol. 2000, 33: 32-37. 10.1016/S0720-048X(99)00105-9.

    Article  CAS  PubMed  Google Scholar 

  14. Eddy DM: Screening for breast cancer. Ann Intern Med. 1989, 111: 389-399. 10.7326/0003-4819-111-5-389.

    Article  CAS  PubMed  Google Scholar 

  15. Lindfors KK, Rosenquist CJ: The cost-effectiveness of mammographic screening strategies. JAMA. 1995, 274: 881-884. 10.1001/jama.1995.03530110043033.

    Article  CAS  PubMed  Google Scholar 

  16. Stout NK, Rosenberg MA, Trentham-Dietz A, Smith MA, Robinson SM, Fryback DG: Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst. 2006, 98: 774-782. 10.1093/jnci/djj210.

    Article  PubMed  Google Scholar 

  17. Anderson BO, Cazap E, El Saghir NS, Yip CH, Khaled HM, Otero IV, Adebamowo CA, Badwe RA, Harford JB: Optimisation of breast cancer management in low-resource and middle-resource countries: executive summary of the Breast Health Global Initiative consensus, 2010. Lancet Oncol. 2011, 12: 387-398. 10.1016/S1470-2045(11)70031-6.

    Article  PubMed  Google Scholar 

  18. Corbex M, Burton R, Sancho-Garnier H: Breast cancer early detection methods for low and middle income countries, a review of the evidence. Breast (Edinburgh, Scotland). 2012, 21: 428-434. 10.1016/j.breast.2012.01.002.

    Article  Google Scholar 

  19. Ginsburg OM, Love RR: Breast cancer: a neglected disease for the majority of affected women worldwide. Breast J. 2011, 17: 289-295. 10.1111/j.1524-4741.2011.01067.x.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Harford JB, Otero IV, Anderson BO, Cazap E, Gradishar WJ, Gralow JR, Kane GM, Niens LM, Porter PL, Reeler AV, Rieger PT, Shockney LD, Shulman LN, Soldak T, Thomas DB, Thompson B, Winchester DP, Zelle SG, Badwe RA: Problem solving for breast health care delivery in low and middle resource countries (LMCs): consensus statement from the Breast Health Global Initiative. Breast (Edinburgh, Scotland). 2011, 20 (Suppl 2): S20-S29.

    Article  Google Scholar 

  21. Autier P, Boniol M, La Vecchia C, Vatten L, Gavin A, Hery C, Heanue M: Disparities in breast cancer mortality trends between 30 European countries: retrospective trend analysis of WHO mortality database. BMJ. 2010, 341: c3620-10.1136/bmj.c3620.

    Article  PubMed  PubMed Central  Google Scholar 

  22. World Bank Country Classification. []

  23. Greene FL, Compton CC, Fritz AG: AJCC Cancer Staging Atlas. 2006, New York: Springer

    Book  Google Scholar 

  24. Drummond MF, Jefferson TO: Guidelines for authors and peer reviewers of economic submissions to the BMJ. The BMJ Economic Evaluation Working Party. BMJ (Clin Res Ed). 1996, 313: 275-283. 10.1136/bmj.313.7052.275.

    Article  CAS  Google Scholar 

  25. Gerard K, Seymour J, Smoker I: A tool to improve quality of reporting published economic analyses. Int J Technol Assess Health Care. 2000, 16: 100-110. 10.1017/S0266462300016196.

    Article  CAS  PubMed  Google Scholar 

  26. Denewer A, Hussein O, Farouk O, Elnahas W, Khater A, El-Saed A: Cost-effectiveness of clinical breast assessment-based screening in rural Egypt. World J Surg. 2010, 34: 2204-2210. 10.1007/s00268-010-0620-3.

    Article  PubMed  Google Scholar 

  27. Ginsberg GM, Lauer JA, Zelle S, Baeten S, Baltussen R: Cost effectiveness of strategies to combat breast, cervical, and colorectal cancer in sub-Saharan Africa and South East Asia: mathematical modelling study. BMJ. 2012, 344: e614-10.1136/bmj.e614.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Groot MT, Baltussen R, Uyl-De Groot CA, Anderson BO, Hortobágyi GN: Costs and health effects of breast cancer interventions in epidemiologically different regions of Africa, North America, and Asia. Breast J. 2006, 12: S81-S90. 10.1111/j.1075-122X.2006.00206.x.

    Article  PubMed  Google Scholar 

  29. Mousavi SM, Harirchi I, Ebrahimi M, Mohagheghi MA, Montazeri A, Jarrahi AM, Gouya MM, Miller AB: Screening for breast cancer in Iran: a challenge for health policy makers. Breast J. 2008, 14: 605-606. 10.1111/j.1524-4741.2008.00662.x.

    Article  PubMed  Google Scholar 

  30. Okonkwo QL, Draisma G, der Kinderen A, Brown ML, de Koning HJ: Breast cancer screening policies in developing countries: a cost-effectiveness analysis for India. J Natl Cancer Inst. 2008, 100: 1290-1300. 10.1093/jnci/djn292.

    Article  PubMed  Google Scholar 

  31. Salomon JA, Carvalho N, Gutierrez-Delgado C, Orozco R, Mancuso A, Hogan DR, Lee D, Murakami Y, Sridharan L, Medina-Mora ME, Gonzalez-Pier E: Intervention strategies to reduce the burden of non-communicable diseases in Mexico: cost effectiveness analysis. Br Med J. 2012, 344: S20-S29. 10.1136/bmj.e20.

    Article  Google Scholar 

  32. Sarvazyan A, Egorov V, Son JS, Kaufman CS: Cost-effective screening for breast cancer worldwide: current state and future directions. Breast Cancer. 2008, 1: 91-99.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Szynglarewicz B, Matkowski R: Low cost of cancer detection in the first year of mammographic screening in Poland. Breast (Edinburgh, Scotland). 2011, 20: 585-10.1016/j.breast.2011.08.135.

    Article  Google Scholar 

  34. Yazihan N, Yilmaz HH: Breast cancer in Turkey: economic efficiency and cost effectiveness. 2006, 740: S20-S29.

    Google Scholar 

  35. Zelle SG, Nyarko KM, Bosu WK, Aikins M, Niens LM, Lauer JA, Sepulveda CR, Hontelez JA, Baltussen R: Costs, effects and cost-effectiveness of breast cancer control in Ghana. Trop Med Int Health. 2012, 17: 1031-1043. 10.1111/j.1365-3156.2012.03021.x.

    Article  PubMed  Google Scholar 

  36. Astim E: Cost-effectiveness analysis of a prospective breast cancer screening program in Turkey. Thesis. 2011, Graduate School of Social Sciences of Middle East Technical University, []

    Google Scholar 

  37. Boutayeb S, Boutayeb A, Ahbeddou N, Boutayeb W, Essaadi I, Tazi M, Errihani H: Estimation of the cost of treatment by chemotherapy for early breast cancer in Morocco. Cost Eff Resour Alloc. 2010, 8: 16-10.1186/1478-7547-8-16.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Fonseca M, Araujo GT, Saad ED: Cost-effectiveness of anastrozole, in comparison with tamoxifen, in the adjuvant treatment of early breast cancer in Brazil. Rev Assoc Med Bras. 2009, 55: 410-415. 10.1590/S0104-42302009000400015.

    Article  PubMed  Google Scholar 

  39. Liubao P, Xiaomin W, Chongqing T, Karnon J, Gannong C, Jianhe L, Wei C, Xia L, Junhua C: Cost-effectiveness analysis of adjuvant therapy for operable breast cancer from a Chinese perspective: doxorubicin plus cyclophosphamide versus docetaxel plus cyclophosphamide. PharmacoEconomics. 2009, 27: 873-886. 10.2165/11314750-000000000-00000.

    Article  PubMed  Google Scholar 

  40. Love RR, Duc NB, Allred DC, Binh NC, Dinh NV, Kha NN, Thuan TV, Mohsin SK, Roanh LD, Khang HX, Tran TL, Quy TT, Thuy NV, Thé PN, Cau TT, Tung ND, Huong DT, Quang LM, Hien NN, Thuong L, Shen TZ, Xin Y, Zhang Q, Havighurst TC, Yang YF, Hillner BE, DeMets DL: Oophorectomy and tamoxifen adjuvant therapy in premenopausal Vietnamese and Chinese women with operable breast cancer. J Clin Oncol. 2002, 20: 2559-2566. 10.1200/JCO.2002.08.169.

    Article  PubMed  Google Scholar 

  41. Munshi A: Resource-sparing and cost-effective strategies in current management of breast cancer. J Canc Res Ther. 2009, 5: 116-120. 10.4103/0973-1482.52797.

    Article  Google Scholar 

  42. Bai Y, Ye M, Cao H, Ma X, Xu Y, Wu B: Economic evaluation of radiotherapy for early breast cancer after breast-conserving surgery in a health resource-limited setting. Breast Cancer Res Tr. 2012, 136: 547-557. 10.1007/s10549-012-2268-1.

    Article  Google Scholar 

  43. Arredondo A, Lockett LY, de Icaza E: Cost of diseases in Brazil: breast cancer, enteritis, cardiac valve disease and bronchopneumonia. Rev Saude Publica. 1995, 29: 349-354.

    Article  CAS  PubMed  Google Scholar 

  44. Kobayashi T: International trends in the economics of breast examination. Ultrasound Med Biol. 1988, 14 (Suppl 1): 217-229.

    Article  PubMed  Google Scholar 

  45. Thomas JO, Amanguno AU, Adeyi OA, Adesina AO: Fine needle aspiration (FNA) in the management of palpable masses in Ibadan: impact on the cost of care. Cytopathology. 1999, 10: 206-210. 10.1046/j.1365-2303.1999.00187.x.

    Article  CAS  PubMed  Google Scholar 

  46. Guggisberg K, Okorie C, Khalil M: Cytopathology including fine-needle aspiration in sub-Saharan Africa: a Cameroon experience. Arch Pathol Lab Med. 2011, 135: 200-206.

    PubMed  Google Scholar 

  47. Nasrinossadat A, Ladan F, Fereshte E, Asieh O, Reza C, Akramossadat S, Golshan M: Marking non-palpable breast masses with injected methylene blue dye, an easy, safe and low cost method for developing countries and resource-limited areas. Asian Pac J Cancer P. 2011, 12: 1189-1192.

    Google Scholar 

  48. Pakseresht S, Ingle GK, Garg S, Singh MM: Expenditure audit of women with breast cancer in a tertiary care hospital of Delhi. Indian J Cancer. 2011, 48: 428-437. 10.4103/0019-509X.92263.

    Article  CAS  PubMed  Google Scholar 

  49. Bastani P, Kiadaliri AA: Cost–utility analysis of adjuvant therapies for breast cancer in Iran. Int J Technol Assess. 2012, 28: 110-114. 10.1017/S0266462312000049.

    Article  Google Scholar 

  50. Gluud LL: Bias in clinical intervention research. Am J Epidemiol. 2006, 163: 493-501. 10.1093/aje/kwj069.

    Article  PubMed  Google Scholar 

  51. Gerkens S, Crott R, Cleemput I, Thissen JP, Closon MC, Horsmans Y, Beguin C: Comparison of three instruments assessing the quality of economic evaluations: a practical exercise on economic evaluations of the surgical treatment of obesity. Int J Technol Assess. 2008, 24: 318-325.

    Article  Google Scholar 

  52. Sculpher MJ, Pang FS, Manca A, Drummond MF, Golder S, Urdahl H, Davies LM, Eastwood A: Generalisability in economic evaluation studies in healthcare: a review and case studies. Health Technol Assess. 2004, 8: 1-192.

    Article  Google Scholar 

  53. Sun X, Wang L, Li Y: Methodological issues in cost-effectiveness studies: a brief overview. J Evid Based Med. 2010, 3: 201-204. 10.1111/j.1756-5391.2010.01098.x.

    Article  PubMed  Google Scholar 

  54. Briggs AH, Claxton K, Sculpher MJ: Decision Modelling for Health Economic Evaluation. 2006, New York: Oxford University Press

    Google Scholar 

  55. Brazier J, Ratcliffe J, Solomon JA, Tsuchia A: Measuring and Valuing Health Benefits for Economic Evaluation. 2007, New York: Oxford University Press

    Google Scholar 

  56. Drummond MF, Sculpher MJ, Torrance GW, O'Brien BJ, Stoddart GL: Methods for the Economic Evaluation of Health Care Programmes. 2005, New York: Oxford University Press, 3

    Google Scholar 

  57. Ramsey S, Willke R, Briggs A, Brown R, Buxton M, Chawla A, Cook J, Glick H, Liljas B, Petitti D, Reed S: Good research practices for cost-effectiveness analysis alongside clinical trials: the ISPOR RCT-CEA Task Force report. Value Health. 2005, 8: 521-533. 10.1111/j.1524-4733.2005.00045.x.

    Article  PubMed  Google Scholar 

  58. Tan-Torres Edejer T, Baltussen R, Adam T, Hutubessy R, Acharya A, Evans DB, Murray CJL: Making Choices in Health: WHO Guide to Cost-effectiveness Analysis. 2003, Geneva: World Health Organization

    Google Scholar 

  59. Lodge M, Corbex M: Establishing an evidence-base for breast cancer control in developing countries. Breast (Edinburgh, Scotland). 2011, 20 (Suppl 2): S65-S69.

    Article  Google Scholar 

  60. Bloom DE, Cafiero ET, Jané-Llopis E, Abrahams-Gessel S, Bloom LR, Fathima S: The Global Economic Burden of Non-communicable Diseases. 2011, Geneva: World Economic Forum, []

    Google Scholar 

  61. Broekx S, Hond ED, Torfs R, Remacle A, Mertens R, D'Hooghe T, Neven P, Christiaens MR, Simoens S: The costs of breast cancer prior to and following diagnosis. Eur J Health Econ. 2011, 12: 311-317. 10.1007/s10198-010-0237-3.

    Article  PubMed  Google Scholar 

  62. Hanly P, Timmons A, Walsh PM, Sharp L: Breast and prostate cancer productivity costs: a comparison of the human capital approach and the friction cost approach. Value Health. 2012, 15: 429-436. 10.1016/j.jval.2011.12.012.

    Article  PubMed  Google Scholar 

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The authors thank Dr Ernst Spaan and Evelinn Mikkelsen for sharing their experience and search strategy on a large health insurance review, which has helped us in setting up our search strategy and with maintaining our search results.

Financial disclosure

No direct funding was received for this study. SGZ and RMB were salaried by their institutions during the period of writing though no specific salary was set aside or given for the writing of this paper. No funding bodies had any role in the study design, data collection, analysis, decision to publish or preparation of the manuscript.

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Correspondence to Sten G Zelle.

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The authors declare that they have no competing interests.

Authors’ contributions

SGZ performed the search strategy, designed the inclusion criteria, reviewed all papers included in the review, developed the evaluation strategy and drafted the manuscript. RMB participated in the design of the study, the selection of relevant articles, the evaluation and classification of articles and contributed to the writing of the manuscript. Both authors reviewed and critically assessed the papers included in this review.

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Zelle, S.G., Baltussen, R.M. Economic analyses of breast cancer control in low- and middle-income countries: a systematic review. Syst Rev 2, 20 (2013).

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